Title: Multi-Agent Social Learning for Market Prediction

Support by: University of Wollongong

Duty: This is a PhD project and I co-supervise the PhD candidate (Mr. Xishun Wang) with Prof. Minjie Zhang. In a large complex Smart Grid market, usually brokers are introduced for power trading. We design an intelligent broker agent—GongBroker, basing on the platform of Power TAC, which simulates a real world Smart Grid market. GongBroker buys energy from the wholesale market through auctions, and sells energy to various consumers in retail market. In our design, we deeply explore the customer consumption behaviors with a data-driven method. All the consumers are clustered according to their historical energy consumptions, and one-day-ahead hourly usage of each consumer cluster is predicted by Logistic regression. Basing on the predicted usages, the auction module employs an MDP process for one-day-ahead auction. To compete with other trading agents, GongBroker uses independent reinforcement learning processes to generate different tariffs for different types of consumers.

Title: Adaptive Resource Allocation Strategies for Emergency Management

Support by: University of Wollongong

Duty: This is a PhD project and I co-supervise the PhD candidate (Mr. Jihang Zhang) with Prof. Minjie Zhang. In emergency management, one of the most important phase is to allocate human resource or materials to mitigate the damage caused by the events. For small-scale emergency events, public emergency services like police force, are department and ambulances can be used to control the damage. But for larger-scale emergency events, the damage control is obviously beyond the capability of these public emergency services. For examples, after a strong earthquake that happened in highly inhabited areas, thousands of people could be killed or affected. Under such situation, the search and rescue in the first few days is extremely important for victims, and it is obvious that separated public emergency services or departments cannot make efficient response if there is no applicable strategies to allocate or coordinate them. One promising way to make fast and effective resource allocation for large-scale emergency events is to use computer science and information technology.

Title: Strengthening Research and Education Collaboration with Dalian University of Technology (DUT) in China

Support by: University of Wollongong ($7,500)

Duty: I am the chief investigator of this project. The aims of this project are (1) to strengthen and broaden current research collaboration between two research teams; (2) to build a long-term partnership between the two institutions by discovering potential opportunities for developing collaborative teaching programs in computer science in both undergraduate and postgraduate levels; (3) to initiate a research training program in a postgraduate level by exchanging visiting research students around the topics of agent-based coordination, learning, negotiation and self-organization; (4) to lead to future joint applications for competitive grants in both countries; and (5) to develop effective mechanisms that will enable autonomous agents to achieve smart management of vehicular networks and Internet of Things (IoT) in open domains through the research collaboration between the Intelligent Systems Research Centre (ISR) at UOW and the Key Research Centre of Internet of Things and Collaborative Sensing (ITCS) at DUT.

 

Title: An Adaptive and Intelligent SLA Negotiation System for Web-Based Service-Oriented Grid Computing

Support by: ARC DECRA ($391,947), University of Wollongong ($184,000)

Duty: I am the chief investigator of this project. Mr. Lei Niu is a PhD candidate (co-supervised with Prof. Minjie Zhang) of this project. This project will develop an intelligent negotiation system for Service Level Agreement (SLA) in web-based service-oriented grid computing. The specific aims include (1) computational models for SLA negotiation representation; (2) intelligent managements of SLA negotiation procedures; and (3) adaptive learning for SLA negotiation system improvement. The significance of this project lies in its promises to realize the automation of SLA negotiation through using intelligent and computational models, so as to greatly improve the efficiency of web-based service systems. The research results will enable software engineers to develop more robust and intelligent service-oriented systems through web-based computational grids.